Pinned Repositories
A-kernel-based-framework-for-learning-KM-coefficients
This computational framework allows the extraction of KM coefficients for arbitrary Markovian diffusion processes and the stochastic jump diffusion process directly from the time series, and is coupled with a symbolic regression algorithm to obtain potential governing equations for the system with its Ito structure.
Data-Driven-GMM-for-FP-Equation
A machine learning method based on an adaptive Gaussian mixture model are proposed to deal with the general FP equations
Koopman-Operator
Neural-PDE-Solver
normalizing-flows
normalizing flows.
PINNpaperreview
PINNpapers
Must-read Papers on Physics-Informed Neural Networks.
JQFeng15's Repositories
JQFeng15/A-kernel-based-framework-for-learning-KM-coefficients
This computational framework allows the extraction of KM coefficients for arbitrary Markovian diffusion processes and the stochastic jump diffusion process directly from the time series, and is coupled with a symbolic regression algorithm to obtain potential governing equations for the system with its Ito structure.
JQFeng15/Data-Driven-GMM-for-FP-Equation
A machine learning method based on an adaptive Gaussian mixture model are proposed to deal with the general FP equations
JQFeng15/Koopman-Operator
JQFeng15/Neural-PDE-Solver
JQFeng15/normalizing-flows
normalizing flows.
JQFeng15/PINNpaperreview
JQFeng15/PINNpapers
Must-read Papers on Physics-Informed Neural Networks.